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Earlier sources: Security
Digital security protects systems, software, accounts, and information from misuse. Explore cybersecurity, vulnerabilities, threat intelligence, cryptography, privacy, and identity, with links to the underlying advisories and research.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗647 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- arXiv · Published · First archived
Tight Query Lower Bounds for Quantum Sampling, with an Application to Certified Randomness ↗
Random circuit sampling experiments, the leading demonstrations of quantum computational advantage, are tested with the linear cross-entropy benchmark (XEB), which scores outcomes by their ideal probabilities. We study what a high XEB score certifies about an untrusted quantum device. In the quantum query model, we show that the honest sampler's ideal score acts as a Tsirelson bound for efficient devices and certified randomness. First, exceeding the ideal score by a constant requires $Ω(N^{1/3})$ queries for the Haar and Fourier oracle ensembles with $N$ outcomes, and this bound is tight; thi…
- GitHub · Repository created · First archived
saisaharsh3/Leftovers ↗
A fast, private expense tracker for Android: log a spend in two taps, see what's safe to spend today, and plan ahead. Data stays on your phone.
- arXiv · Published · First archived
Differentially Private Mixing of Public Datasets Improves Private Learning ↗
Many machine learning applications involve sensitive data and therefore require training under differential privacy (DP). However, DP training often degrades model utility. In some cases, first pre-training the model on "public" data before finetuning with DP on the sensitive data can reduce the drop in utility. However, the success of this depends on how relevant the selected public dataset is to the sensitive data. We introduce the first pipeline that privately learns the mixture of several public datasets to pretrain on for a given sensitive downstream task. Our key insight is that we can p…
- GitHub · Repository created · First archived
SoonGwan/open-aegis ↗
Self-hosted open source security validation workspace: approved scope, evidence and independent retests
- arXiv · Published · First archived
Does AI Help Cyber Attackers or Defenders? Evidence from Nonpublic Vulnerabilities and Subsequent Attacks ↗
The release decision for frontier AI systems increasingly relies on cyber capability benchmarks, yet public vulnerability benchmarks can expose agents to previously published advisories, exploits, and fixes, making it difficult to distinguish prior exposure from capability on unseen vulnerabilities. We evaluate open-weight and proprietary AI models on exploit generation, vulnerability repair and subsequent attacks in five nonpublic software environments, including vulnerabilities we privately disclosed while they remained unpatched. Researcher-developed and reviewed deterministic graders, not…
- arXiv · Published · First archived
GCTAuto-encoder: A Cross modal Framework for Security Flaw Detection in IoT Networks ↗
IoT encompasses diverse physical entities, from smart home devices to autonomous vehicles, creating a complex environment with heterogeneous security models. This heterogeneity makes IoT sub-systems vulnerable to various network attacks. Modern security systems must therefore be more robust to ensure security and privacy for IoT applications. A highly secure IoT system also demands real time insight, requiring data collection at the edge of the computing layer. This diversity calls for a unified security model applied at the foundational level. Edge intelligence offers a direct approach to han…
- arXiv · Published · First archived
An Evaluation of the Semantic Understanding Capabilities of Large Language Models for Web Attack Payloads ↗
Computer vision services delivered through Web interfaces and APIs process textual requests for image-resource acquisition, inference-task configuration, and result management, making Web attack-payload analysis relevant to their deployment security. Large language models (LLMs) can identify payload types and explain attack intent. However, existing studies generally treat payload analysis as a single-layer classification task and lack both a systematic assessment of how deeply LLMs understand payloads and an evaluation benchmark dedicated to the depth of semantic understanding of Web attack p…
- GitHub · Repository created · First archived
InvisiProxy/InvisiProxyLTS ↗
InvisiProxy LTS is a web proxy service (website) that helps you access websites that may be blocked by your network, government or policy all within your browser with no downloads. It does this securely and with additional privacy features. Browse Tor/Onion sites in any browser, hide browsing activity and bypass filters. (Star if you fork it!)
- Hacker News · Posted on Hacker News · First archived
Meta Rushed to Fix Muse 'VM Escape' Vulnerability Soon Before Launch ↗
Hacker News discussion.
- arXiv · Published · First archived
Terracotta: Enabling the Adoption of New DRAM Techniques via a Flexible DRAM Interface and Memory Controller ↗
DRAM continues to limit the performance, energy efficiency, and robustness of modern systems. Many prior works propose DRAM techniques that support in-DRAM computation, improve memory access latency and parallelism, and enhance DRAM maintenance and reliability. However, adopting each new technique requires repeated modifications to the rigid DRAM interface and memory controller, hindering its deployment. Our goal is to reduce these repeated modifications. We observe that the DRAM commands and memory controller structures of many DRAM techniques are similar. Our key idea is to use these similar…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Security
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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